Dr Arkady Konovalov MA, PhD

Dr Arkady Konovalov

School of Psychology
Associate Professor

Arkady Konovalov is a neuroeconomist interested in studying individual and social decision making using models of the choice process and value-based learning, applying methods of computational neuroscience such as response times modeling, fMRI, EEG, eye-tracking, and mouse-tracking.


PhD in Economics, The Ohio State University

MA in Economics, The Ohio State University


Arkady Konovalov obtained his MA and PhD degrees from the Ohio State University, where he received training in behavioral economics and cognitive psychology, working with Ian Krajbich, PJ Healy, and John Kagel. He then completed his postdoctoral training in decision neuroscience with Christian Ruff at the University of Zurich.

Postgraduate supervision

PhD Students interested in working on projects in neuroeconomics with Dr Konovalov should contact him regarding potential funding opportunities.

Dr Konovalov is also interested in working with postdocs who have training in decision making, computational modeling, and fMRI.


Neuroeconomics, decision neuroscience, social neuroscience, behavioral economics, experimental economics, social interactions, strategic decisions, reinforcement learning, computational modeling, fMRI, EEG, eye tracking, mouse tracking.


  1. Konovalov, A. & Ruff, C.C. (2022). Enhancing Models of Social and Strategic Decision Making with Process Tracing and Neural Data. WIREs Cognitive Science, 13:e1559.
  2. Konovalov, A.*, Hill, C.*, Daunizeau, J., & Ruff, C.C.  (2021). Dissecting the Functional Contributions of the Social Brain to Strategic Behavior. Neuron, 109, 3323–333.
  3. Konovalov, A., & Krajbich, I. (2020). Mouse Tracking Reveals Structure Knowledge in the Absence of Model-Based Choice. Nature Communications, 11.
  4. Konovalov, A., & Krajbich, I. (2019). Revealed Strength of Preference: Inference from Response Times. Judgement and Decision Making, 14(4), 381-394.
  5. Konovalov, A., & Krajbich, I. (2019). A Decade of Neuroeconomics: What Have We Learned? Organizational Research Methods, 22(1), 148-173.
  6. Konovalov, A., & Krajbich, I. (2018). Neurocomputational Dynamics of Sequence Learning. Neuron, 98(6), 1282-1293.
  7. Konovalov, A.*, Hu, J.*, & Ruff, C.* (2018). Neurocomputational Approaches to Social Behavior. Current Opinion in Psychology, 24, 41-47.
  8. Konovalov, A., & Krajbich, I. (2016). Gaze Data Reveal Distinct Choice Processes Underlying Model-Based and Model-Free Reinforcement Learning. Nature Communications, 7.

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